In a conventional downlink multiplex cellular communication system in which BSs share the same frequency resources, each BS determines the power thereof such that the power does not exceed a peak power assigned thereto only considering channel states of user equipments (UEs) belonging thereto regardless of other BSs.
However, allocation of power to a BS using this method causes problems in a system using frequency reuse factor of 1. When a UE is located at a cell edge far away from a BS, signal power is weakened due to signal attenuation according to distance in a radio channel environment and communication performance is remarkably deteriorated by interference signals from other BSs. Accordingly, the UE located at the cell edge (referred to as a cell edge UE hereinafter) is difficult to be provided with high quality communication services.
To solve these problems, researches on a cell cooperation method have been actively carried out recently. Management of cell edge UEs through cell cooperation can help provide better communication services to the cell edge UEs. However, the cell cooperation method requires excessive information exchange between BSs through backhaul and calculations with high complexity. Therefore, researches on feasible information exchange and an algorithm having low complexity are needed.
An interference signal coming from a neighboring BS most largely affects the performance of a UE on downlink. Since the power of the neighboring BS is an important factor that constitutes the interference signal affecting the UE, appropriate control of the power of the neighboring BS is very important for improvement of system performance as well as performance of cell edge UEs.
To implement, there has been studied a method for controlling transmit power to enhance fairness for neighboring BSs in a cellular mobile communication system. According to this method, BSs separate responses to traffic transmitted to UEs into ACK signals and NACK signals and receive the ACK signals and the NACK signals from the UEs such that a BS for which NACK signals are generated most frequently transmits signals with as high power as possible and a BS for which a lowest number of NACK signals are generated transmits signals with as low power as possible on the basis of the percentage of the NACK signals in the whole traffic.
Neighboring BSs share the percentage of NACK signals. In view of this, there was a proposed a method for reducing magnitudes of interference signals generated from neighboring BSs through cooperation between neighboring BSs to improve fairness among cells. That is, the above-mentioned conventional method calculates transmit power of a BS using a transmit power transmission coefficient calculated by the BS in response to whether or not data has been successfully transmitted to a UE from the BS and exchanges the calculated transmit power between neighboring BSs so as to achieve fairness between cells through a negotiation between the cells.
In this conventional method, data is coded and transmitted according to a given channel state in the actual communication environment. Here, a coding rate plays an important role in successfully transmitting data. However, successful data transmission depends on how the coding rage is appropriately determined in response to the channel state, and thus it is not appropriate to discuss fairness on the basis of success or failure in transmitting data to each cell in the actual communication environments.
Furthermore, considering a communication system that satisfies minimum average transmission rates of UEs, the aforementioned conventional method cannot meet the condition of this communication system. Moreover, even though fairness of one cell can be discussed on the basis of success or failure in transmitting data to the cell in the conventional method, if a negotiation is conducted between cells to reduce the power of a neighbor cell on the basis of a cell in a poor state, the maximum power of a neighboring cell which does not need power control is also decreased.
Since a degree of influence of a neighboring cell on UEs belonging to a certain cell depends on locations of the UEs, if the certain cell can distinguish a cell having a great influence thereon, reducing the maximum power of the cell is much more efficient than decreasing power of all neighboring cells.
Therefore, the aforementioned conventional method has problems of limiting the average transmission rate of a concerned cell so as to bring about deterioration of the performance of the overall system because it restricts even the power of a neighboring cell which barely affects the concerned cell. It is necessary to conduct negotiations based on calculation results of BSs in consideration of many factors in a state the BSs share as much information about them as possible. However, the above-described conventional method processes information including only feedback information on UEs belonging to BSs and conducts a negotiation between the BSs using the processed information. Accordingly, a proper negotiation cannot be performed since the BSs cannot be aware of information abut the other BSs.
As described above, conventional technologies have many problems. In addition, there have not been proposed a BS power control method and a BS device using the same for securing fairness among cells, particularly, a minimum average transmission rate of a cell edge UE and efficiently determining powers of BSs through information sharing between BSs in a down link multiplex cellular system.
A cellular system, which is a concept suggested to overcome limit of a service area and a restriction on subscriber capacity, divides a service area into small areas, that is, cells or sectors, and uses the same frequency band for two cells located sufficiently apart from each other to achieve spatial frequency reuse. A cell means a service area covered by one radio BS and a plurality of cells constitutes a service area corresponding to one system.
The cellular system has characteristics of frequency reuse, cell segmentation, handoff (or handover), etc. The cellular system uses the same frequency for different cells to maximize subscriber capacity. At this time, a frequency reuse distance depends on topographical characteristics, antenna height, transmit power, etc. Cell segmentation is one of methods for maximizing the subscriber capacity. Cells in the cellular system are independent areas having different channels and generate a call path at the request of a subscriber.
In a multiplex cellular system, each cell assigns radio resources including time, frequency and power to each UE in consideration of only itself. When communication is carried out between a BS and a UE, communication performance may be deteriorated due to interferences from neighboring cells using the same time and frequency band as those of the cell including the UE. Communication performance deterioration may be aggravated as the distance between the UE and a cell edge decreases.
This communication performance deterioration may become a problem in not only a current multiplex cellular system but also a next-generation mobile communication system expected to have an increasing number of small- and medium-sized cells such as femto-cells, pico-cell and the like. To provide a fast data service with stability, it is necessary to effectively overcome interferences from neighboring cells irrespective of locations of UEs or channel states.
Recently, researches on multi-cell cooperative communication have been actively carried out in order to overcome the communication performance deterioration. As a representative research result, M. K. Karakayali et al. proposed a scheme of performing dirty paper coding among BSs to maximize minimum transmission rates of UEs during signal transmission considering BSs and UEs belonging to multiple cells as virtual multiple-input and multiple-output (MIMO) systems, which is described in “On the maximum common rate achievable in a coordinated network” published in “IEEE International Conference on Communications (ICC)” in 2006.
The scheme proposed in the above paper can effectively reduce the influence of interference and obtain diversity gain so as to maximize efficiency of utilization of radio resources and considerably improve a minimum transmission rate of a UE in a poor channel state.
Dirty paper coding, one of previous interference signal removal technologies, enables a transmitting side to previously remove an interference signal when the transmitting side is aware of the interference signal such that a receiving side is not affected by the interference signal. This coding technique is drawing attention as a scheme of theoretically securing capacity in a Gaussian downlink environment having multi-user MIMO.
In general, two independent codes are used to implement dirty paper coding. One of them is an error correcting code used to restore original information from a received signal damaged by a channel and the other is a shaping code capable of minimizing power consumption of a transmitting side by shaping transmitted signals into a form similar to a square. A receiver can gradually increase decoding reliability by using an iterative decoding scheme between two decoders corresponding to the two codes. A dirty paper coding system implemented in this manner has performance which approximates Shannon limit.
A description will be given of a conventional method for performing dirty paper coding on a signal and transmitting the coded signal, to thereby maximize minimum transmission rates of UEs.
Each cell selects a UE according to an arbitrary scheduling scheme (step 1). Each BS transmits information on current channel states between the BS and selected UEs and information on signals transmitted to the UEs to other BSs in a cooperative unit, a representative BS which performs dirty paper coding, or a radio network controller (referred to as RNC hereinafter) (step 2).
Each BS, the representative BS performing dirty paper coding or the RNC performs dirty paper coding which maximizes minimum transmission rates of the UEs selected in step 1 in a virtual MIMO system environment created between BSs in the cooperative unit and the UEs using the information transmitted from step 2 (when an arbitrary BS or the RNC acts as a representative to perform dirty paper coding, it transmits information regarding execution of the dirty paper coding to the BSs in the cooperative unit) (step 3). Then, each BS transmits a signal in response to the scheduling and dirty paper coding results (step 4).
The above-mentioned method supposes a communication system capable of performing joint processing between BSs in the cooperative unit in order to use the dirty paper coding. Accordingly, each BS needs to exchange an excessive amount of information including current channel state information and transmission signal information with respect to all UEs, information regarding execution of dirty paper coding and the like with other BSs or a device acting as a representative to perform dirty paper coding in the cooperative unit at every scheduling interval.
It is difficult to use dirty paper coding for optimized radio resource management in practice since a massive amount of calculations are required to perform the dirty paper coding and complexity of the calculations is considerably high. Furthermore, since UEs are allocated prior to dirty paper coding, it is impossible to simultaneously consider minimum transmission rates of all UEs belonging to a cooperative unit when each cell includes a plurality of UEs.
There has not been proposed an efficient cell cooperative radio resource management method capable of securing minimum transmission rates of all UEs belonging to a cooperative unit and considering proportional fairness while having an overhead and complexity permissible in a practical system.